Nathan Phelps
Nathan Phelps is a PhD student in Statistics at Western University, where he is a member of both the Wildland Fire Science Lab and the PHI Lab. Nathan has a BSc in Actuarial Science and Data Science and a MSc in Computer Science. After completing his MSc, he worked as a Research Associate in the Wildfire Analytics Lab at the University of Alberta, then joined the Financial Wellness Lab as a data engineer. He has transitioned to a part-time role in the lab during his PhD studies.
Areas of Interest
Applying statistical and machine learning techniques to problems in personal finance, wildland fire science, and health care.
Publications
Phelps N, Metzler A (2024) An exploratory clustering analysis of the 2016 National Financial Well-Being Survey. PLoS ONE 19(9): e0309260. https://doi.org/10.1371/journal.pone.0309260
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Phelps, N. & Metzler, A. (2023). Enhancing an existing algorithm for small-cardinality constrained portfolio optimisation. Journal of the Operational Research Society, 1-15.
Phelps, N. & Beverly, J. L. (2022). Classification of forest fuels in selected fire-prone ecosystems of Alberta, Canada—implications for crown fire behaviour prediction and fuel management. Annals of Forest Science, 79(1), 40.
Phelps, N., Cameron, H., Forbes, A. M., Schiks, T., Schroeder, D., & Beverly, J. L. (2022). The Alberta Wildland Fuels Inventory Program (AWFIP): data description and reference tables. Annals of Forest Science, 79(1), 28.
Phelps, N. & Woolford, D. G. (2021). Comparing calibrated statistical and machine learning methods for wildland fire occurrence prediction: A case study of human-caused fires in Lac La Biche, Alberta, Canada. International Journal of Wildland Fire, 30(11), 850-870.
Arntfield, R., VanBerlo, B., Alaifan, T., Phelps, N., White, M., Chaudhary, R., Ho, J., & Wu, D. (2021). Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study. BMJ Open, 11(3), e045120.
Phelps, N. & Woolford, D. G. (2021). Guidelines for effective evaluation and comparison of wildland fire occurrence prediction models. International Journal of Wildland Fire, 30(4), 225-240.
Contact
Email address: nphelps3@uwo.ca